https://github.com/laavanjan/enhanced-qa-chatbot-with-ollama
https://github.com/laavanjan/enhanced-qa-chatbot-with-ollama
Last synced: 7 months ago
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- Host: GitHub
- URL: https://github.com/laavanjan/enhanced-qa-chatbot-with-ollama
- Owner: laavanjan
- Created: 2025-02-15T13:23:10.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2025-02-15T13:55:07.000Z (8 months ago)
- Last Synced: 2025-02-15T14:26:55.360Z (8 months ago)
- Language: Python
- Size: 110 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Enhanced-QA-Chatbot-With-Ollama 🤖
This repository contains an enhanced Question Answering (QA) chatbot built using LangChain, Ollama, Python, Streamlit, and LangSmith. It offers the capability to switch between two different language models: "llama3.2" and "gemma:2b". 🧠
## Overview
This chatbot leverages the power of Ollama to run large language models locally. 🏠 It provides a user-friendly interface through Streamlit, allowing users to interact with the chosen model for question answering tasks. LangChain facilitates the integration of different components and provides powerful tools for chain-of-thought prompting and other advanced features. LangSmith is used for experiment tracking and evaluation of the chatbot performance. 📈
## Technologies Used
* **LangChain:** Framework for building applications with LLMs. ⛓️
* **Ollama:** Tool for running and managing Large Language Models locally. 🦙
* **Python:** Programming language used for development. 🐍
* **Streamlit:** Framework for creating interactive web applications. streamlit
* **LangSmith:** Platform for debugging, testing, and evaluating LLM applications. 🔬
* **llama3.2:** One of the supported language models.
* **gemma:2b:** The other supported language model.
## Features
* **Model Switching:** Easily switch between the "llama3.2" and "gemma:2b" models. 🔄
* **User-Friendly Interface:** Interactive web interface built with Streamlit. ✨
* **Local LLM Execution:** Leverages Ollama for running models locally, ensuring privacy and potentially faster inference. 🔒
* **LangChain Integration:** Utilizes LangChain for advanced prompting techniques and chain management. 🚀
* **Experiment Tracking:** Uses LangSmith for experiment tracking and evaluation. 📊
## Installation
1. **Clone the repository:**
```bash
git clone [https://github.com/laavanjan/Enhanced-QA-Chatbot-With-Ollama.git](https://github.com/laavanjan/Enhanced-QA-Chatbot-With-Ollama.git)
cd Enhanced-QA-Chatbot-With-Ollama
```
2. **Install dependencies:**
```bash
pip install -r requirements.txt
```
3. **Install Ollama and download the models:**
Follow the instructions on the [Ollama website](https://ollama.ai/) to install Ollama. Then, download the "llama3.2" and "gemma:2b" models. Make sure Ollama is running. ✅
4. **Set up LangSmith:**
Create an account on LangSmith and obtain your API key. Set the environment variables `LANGSMITH_API_KEY` and optionally `LANGSMITH_HOST` as described in the LangSmith documentation. 🔑
## Usage
1. **Run the Streamlit application:**
```bash
streamlit run app.py
```
2. **Access the application:**
Open your web browser and navigate to the URL provided by Streamlit (usually `http://localhost:8501`). 🌐
3. **Interact with the chatbot:**
Use the interface to ask questions and switch between the available models. 💬
## Contributing
Contributions are welcome! 🎉 Please open an issue or submit a pull request. 🤝
## License
This project is licensed under the GPL License - see the [LICENSE](LICENSE) file for details. 📜
## Acknowledgements
Leave a like 👍 if you found it useful! 😊